Discovering group nonverbal conversational patterns with topics

This paper addresses the problem of discovering conversational group dynamics from nonverbal cues extracted from thin-slices of interaction. We first propose and analyze a novel thin-slice interaction descriptor - a bag of group nonverbal patterns - which robustly captures the turn-taking behavior of the members of a group while integrating its leader's position. We then rely on probabilistic topic modeling of the interaction descriptors which, in a fully unsupervised way, is able to discover group interaction patterns that resemble prototypical leadership styles proposed in social psychology. Our method, validated on the Augmented Multi-Party Interaction (AMI) meeting corpus, facilitates the retrieval of group conversational segments where semantically meaningful group behaviours emerge, without the need of any previous labeling. Categories and Subject Descriptors H.3.1 [Information Storage and Retrieval]: Content Analysis and Indexing General Terms Human Factors Keywords Meetin...

• Type: Journal
• Year: 2009
• Where: ICMI
• Authors: Dinesh Babu Jayagopi, Daniel Gatica-Perez
• Keywords: Biometrics, Group, ICMI 2009, Nonverbal Cues, Thin-slice Interaction Descriptor